Exploring Indigenous Spiritualities In-Relation: How Might Science and Math Education Become Different?
Bibliographic record
Abstract
The idea for this symposium took shape at the last CSSE Meeting in Toronto, where a discussion of ecoliteracy seemed to meander around questions and explorations of spirituality. This symposium attempts to put Indigenous Spiritualities in relation with education subfields (math and science education), which may often operate in a technical rational mindset, culture, and/or set of practices. The authors/presenters come together to engage this topic from a variety of perspectives in mathematics and science education to see how education, especially those subfields that often adhere strongly to Modern Western Ways of knowing, might open to different relational and significant ways of being in and knowing the world. This kind of epistemic and pedagogical opening will also require an openness to seriously engage in decolonizing work and an education that seeks more ecologically attentive, imaginative, and just ways of living in the world. We collectively affirm that engaging the spiritual in education is an essential part of learning to live differently in deeply troubled times and spaces.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.034 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".